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Learning Quantitative Finance with R

You're reading from   Learning Quantitative Finance with R Implement machine learning, time-series analysis, algorithmic trading and more

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781786462411
Length 284 pages
Edition 1st Edition
Languages
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Authors (2):
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PRASHANT VATS PRASHANT VATS
Author Profile Icon PRASHANT VATS
PRASHANT VATS
Dr. Param Jeet Dr. Param Jeet
Author Profile Icon Dr. Param Jeet
Dr. Param Jeet
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to R 2. Statistical Modeling FREE CHAPTER 3. Econometric and Wavelet Analysis 4. Time Series Modeling 5. Algorithmic Trading 6. Trading Using Machine Learning 7. Risk Management 8. Optimization 9. Derivative Pricing

Questions


  1. What is the significance of optimization in quant finance?

  2. What is the dynamic rebalancing optimization method? Give an example of how to execute it in R.

  3. How can a grid search be used to fine-tune a classification model? Please provide an example in R.

  4. How can genetic algorithm be used in R for optimizing a trading algorithm?

  5. How can genetic algorithm be used in R for estimating a model coefficient in R? Provide an example.

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